Satellite Sea Surface Temperature Observations Research Articles

Learning Sea Surface Height Interpolation From Multi‐Variate Simulated Satellite Observations

AbstractSatellite‐based remote sensing missions have revolutionized our understanding of the Ocean state and dynamics. Among them, space‐borne altimetry provides valuable Sea Surface Height (SSH) measurements, used to estimate surface geostrophic currents. Due to the sensor technology employed, important gaps occur in SSH observations. Complete SSH maps are produced using linear Optimal Interpolations (OI) such as the widely used Data Unification and Altimeter Combination System (duacs). On the other hand, Sea Surface Temperature (SST) products have much higher data coverage and SST is physically linked to geostrophic currents through advection. We propose a new multi‐variate Observing System Simulation Experiment (OSSE) emulating 20 years of SSH and SST satellite observations. We train an Attention‐Based Encoder‐Decoder deep learning network (abed) on this data, comparing two settings: one with access to ground truth during training and one without. On our OSSE, we compare abed reconstructions when trained using either supervised or unsupervised loss functions, with or without SST information. We evaluate the SSH interpolations in terms of eddy detection. We also introduce a new way to transfer the learning from simulation to observations: supervised pre‐training on our OSSE followed by unsupervised fine‐tuning on satellite data. Based on real SSH observations from the Ocean Data Challenge 2021, we find that this learning strategy, combined with the use of SST, decreases the root mean squared error by 24% compared to OI.

CO2 fluxes under different oceanic and atmospheric conditions in the Southwest Atlantic Ocean

The Southwest Atlantic Ocean (SAO) is one of the largest global carbon sink areas. Therefore, the main objective of this study is to investigate turbulent CO2 flux behavior and quantify it in the presence of an intense horizontal sea surface temperature (SST) gradient in the SAO under different atmospheric conditions. In-situ, satellite, and reanalysis data were used from October 14 to 27, 2018 to achieve this objective. The study area was divided into four areas based on satellite observations of SST, salinity, and chlorophyll. The CO2 flux was calculated using the eddy covariance method. During the experiment the area absorbing the most CO2 was the Brazil Current (BC) owing to its proximity to the chlorophyll-rich and less saline waters of the La Plata River and the cold and less saline waters from the Malvinas Current (MC). Moreover, intense wind speeds increased the CO2 flux between the ocean and atmosphere. The Brazil Malvinas Confluence (BMC) also behaved as a CO2 sink, and the modulation of CO2 fluxes was due to the intense horizontal gradient of SST together with the moderate surface wind and turbulence. During the experiment, the MC sequestered less carbon than other regions because of the presence of high-pressure atmospheric systems near the region, resulting in high atmospheric stability, that inhibited mass exchange between the ocean and atmosphere. Vertical mixing mechanisms were identified at the BMC on the cold side, over MC waters. However, in the BC waters, the marine atmospheric boundary layer was modulated by the high-pressure atmospheric system, which suppressed the turbulent mixing. However, the intense mass exchange between the ocean and atmosphere was inhibited, and the area behaved as a mild CO2 sink because of the high-pressure system. This research contributes to a better understanding of the role of the SAO in the global carbon balance in a climate change scenario, and we showed that area can act as a CO2 sink or source, depending on the large-scale atmospheric conditions acting.

Vertical extrapolation of Advanced Scatterometer (ASCAT) ocean surface winds using machine-learning techniques

Abstract. The increasing demand for wind energy offshore requires more hub-height-relevant wind information, while larger wind turbine sizes require measurements at greater heights. In situ measurements are harder to acquire at higher atmospheric levels; meanwhile the emergence of machine-learning applications has led to several studies demonstrating the improvement in accuracy for vertical wind extrapolation over conventional power-law and logarithmic-profile methods. Satellite wind retrievals supply multiple daily wind observations offshore, however only at 10 m height. The goal of this study is to develop and validate novel machine-learning methods using satellite wind observations and near-surface atmospheric measurements to extrapolate wind speeds to higher heights. A machine-learning model is trained on 12 years of collocated offshore wind measurements from a meteorological mast (FINO3) and space-borne wind observations from the Advanced Scatterometer (ASCAT). The model is extended vertically to predict the FINO3 vertical wind profile. Horizontally, it is validated against the NORwegian hindcast Archive (NORA3) mesoscale model reanalysis data. In both cases the model slightly over-predicts the wind speed with differences of 0.25 and 0.40 m s−1, respectively. An important feature in the model-training process is the air–sea temperature difference; thus satellite sea surface temperature observations were included in the horizontal extension of the model, resulting in 0.20 m s−1 differences with NORA3. A limiting factor when training machine-learning models with satellite observations is the small finite number of daily samples at discrete times; this can skew the training process to higher-/lower-wind-speed predictions depending on the average wind speed at the satellite observational times. Nonetheless, results shown in this proof-of-concept study demonstrate the limited applicability of using machine-learning techniques to extrapolate long-term satellite wind observations when enough samples are available.

Climate-induced changes in temperature, salinity, and sound speed in the global ocean

Oceans play a significant role in climate change by absorbing the earth's excess heat and transporting heat from one location to another. Melting and reducing ice coverage, rising sea levels, ocean acidification, and changes in underwater sound propagation are a few impacts of global warming on oceans. Marine lives have been threatened by many of these alterations, such as interference of their communications and reduction of their habitable places, resulting in the ocean ecosystem imbalance. Ocean datasets containing temperature and salinity are necessary to measure the warming rates and places, access the magnitude and extent of the impacts, and consider mitigation policies. Data collected by traditional in situ measurement techniques are insufficient for this purpose because of the scarcity of the measurements in the vast ocean. Here, an idea to overcome the limitation is proposed by using machine learning to infer the ocean temperature and salinity from satellite-observed sea surface temperature and salinity data that are broadly available. Following the predicted temperature and salinity values, global warming indicators, such as ocean heat content and mixed layer depth, are examined. Also examined are the underwater sound speed variations.

Extreme cooling of 12.5 °C triggered by Typhoon Fungwong (2008)

Typhoon Fungwong, a category-2 but deadly typhoon in the 2008 Pacific typhoon season, made landfall first on Taiwan and then on Southeast China. During its approach toward Taiwan, it triggered an extreme sea surface temperature (SST) drop of 12.5 °C, which was the strongest SST drop recorded by Longdong buoy northeast of Taiwan coast from 1998 to 2017. In this study, including moored buoy temperature measurements, Argo float temperature profiles, satellite-observed SSTs, and a suite of numerical experiments performed using the Regional Ocean Modeling System were used to unveil the detailed processes of how Fungwong triggered such an extreme cooling. Subsequently, the source of the cold waters feeding the extreme cooling, possible mechanisms triggering the cooling, and consequential effects of cooling on the ambient ocean environment were systematically investigated. Results show that the extreme cooling was triggered mainly by a process of uplift of subsurface cold water tied to shore-ward Kuroshio intrusion driven by easterly/northeasterly winds and consequential entrainment mixing, while coastal upwelling driven by persistent longshore (southerly) winds plays a minor role. Nevertheless, the southerly winds still help the enhancement of entrainment mixing and thus the sea surface cooling. Finally, modeled float trajectories with temperature tracers identified where the cold water goes and indicate that the temperature drop might extend all the way toward the south end of Japan (Kyushu) along the flowing path of Kuroshio.

Interannual variation of coastal upwelling around Hainan Island

Coastal upwelling around Hainan Island has a significant impact on the physical environment, ecological environment, and fishery resources of the surrounding waters. Based on the satellite-observed sea surface temperature (SST) from 2003 to 2021, this study analyzed the interannual variations of SST around Hainan Island and the influence of the sea surface forcing on them, with special attention to the upwelling regions in Qiongdong and Qiongxi. The results show that satellite-observed SST can identify three upwelling regions located in the west (WS), east (ES), and northeast (NES) sides of the Hainan Island. The SSTs in the WS, ES, and NES showed warming trends of 0.045 °C/y, 0.010 °C/y, and 0.036 °C/y, respectively. The range of low-temperature water around Hainan Island has gradually shrunk over the past two decades, and this shrinkage trend was more prominent in the WS upwelling region than in the ES and NES upwelling regions. Both the EOF analysis and the SST difference between upwelling regions and non-upwelling regions suggests that the upwelling becomes stronger after 2013. However, it seems not to compete with the overall SST warming in the northwest area of the South China Sea. The interannual SST variations in the ES upwelling region were affected by the local wind stress curl in summer. Except for the wind stress curl, the interannual SST variations in NES upwelling are influenced by the stratification associated with local precipitation and wind direction, especially in 2018. In addition, the interannual SST variation in the WS upwelling region is closely related to the bottom cold water in the central Gulf of Tonkin, which was preserved from the previous winter and is influenced by winter atmospheric conditions. These results are helpful for understanding the variations in SST and ecosystem in the upwelling regions around Hainan Island.

Upper Ocean Responses to the Tropical Cyclones Ida and Felicia (2021) in the Gulf of Mexico and the Eastern North Pacific

Tropical cyclones (TCs) are a significant component of ocean–atmosphere interactions and the climate system. These interactions determine both the development and strength of TCs, as well as various biogeochemical processes in the upper oceans, including vertical mixing and primary production. We investigated the impact of the TCs Felicia and Ida that emerged in 2021 in the eastern North Pacific and the Gulf of Mexico, respectively, using satellite observations of sea-surface temperature (SST) and surface chlorophyll a (chl-a) concentrations, and vertical profiles of temperature and salinity derived from Argo floats. Observations differed between the two study areas. Cooling of SST associated with TC Ida was observed throughout the Gulf of Mexico (<0.5 °C), except for warming in a region off the Mexican coast east of Ida’s track (by about 0.5 °C). The passing of TC Felicia cooled SST in the eastern region (15°N, 115°W) and a central region (15°N, 125°W) by 0.5 °C and 0.36 °C, respectively. The passing of the TCs caused enhanced vertical mixing of the upper ocean layer in the Gulf of Mexico, with a deepening of the mixed layers from 38 m to 68 m (TC Ida). In contrast, the mixed layer in the eastern North Pacific decreased from 50 m to 20 m. For the eastern North Pacific, mixing could be related to an increase in surface chl-a and thus enhanced phytoplankton biomass was observed for 2 months after the passing of TC Felicia with a chl-a increase of 0.15 mg m−3. In the Gulf of Mexico, however, TC Ida caused the injection of a coastal phytoplankton bloom into the open Gulf, resting for more than a month after the cyclone had passed. Our findings contribute to the understanding of potential SST cooling, destratification, and enhanced primary production due to the passage of TCs in two distinct ocean regions, i.e., the open eastern North Pacific and the semi-enclosed Gulf of Mexico.

Marine Heatwaves Characteristics in Spermonde Islands, West Coast of South Sulawesi, Indonesia

Marine heatwaves (MHWs) have caused devastating impacts on marine communities, especially on coastal ecosystems. A coral reef is a coastal community that is vulnerable to changes in the marine environment, especially sea surface temperature. This study focused on investigating the characteristics of MHWs in the Spermonde Islands (SI), which is home to coral reef communities. The dynamics of MHWs were examined during the cold phase of the Pacific Decadal Oscillation (PDO) in recent years (2008–2021) using satellite-observed sea surface temperature data provided by National Oceanic and Atmospheric Administration (NOAA). Statistical methods calculated the characteristics of MHWs such as frequency, intensity, and duration. The analysis results showed that frequency of occurrence, mean maximum intensity, and mean duration of MHWs in the SI were around three times a year, 0.9–1.5 °C, and 8–12 days, respectively. The linear trend of frequency of occurrence of MHWs in the SI showed a decrease of 1 event per decade. In contrast, the linear trend of maximum intensity and duration of MHWs showed an increasing trend in the SI. In addition, this study also showed that the MHWs characteristics in the SI were controlled remotely by El Niño Southern Oscillation (ENSO) climate phenomena. Towards the end of the strong El Niño periods, notably in 2016, the MHWs occurred longer and more intensely.

Small‐Scale Spatial Variations of Air‐Sea Heat, Moisture, and Buoyancy Fluxes in the Tropical Trade Winds

AbstractObservations from two autonomous Wave Gliders and six Lagrangian Surface Wave Instrument Float with Tracking drifters in the northwestern tropical Atlantic during the January–February 2020 NOAA Atlantic Tradewind Ocean‐atmosphere Mesoscale Interaction Campaign (ATOMIC) are used to evaluate the spatial variability of bulk air‐sea heat, moisture, and buoyancy fluxes. Sea surface temperature (SST) gradients up to 0.7°C across 10–100 km frequently persisted for several days. SST gradients were a leading cause of systematic spatial air‐sea sensible heat flux gradients, as variations over 5 Wm−2 across under 20 km were observed. Wind speed gradients played no significant role and air temperature adjustments to SST gradients sometimes acted to reduce spatial flux gradients. Wind speed, air temperature, and air humidity caused high‐frequency spatial and temporal flux variations on both sides of SST gradients. A synthesis of observations demonstrated that fluxes were usually enhanced on the warm SST side of gradients compared to the cold SST side, with variations up to 10 Wm−2 in sensible heat and upward buoyancy fluxes and 50 Wm−2 in latent heat flux. Persistent SST gradients and high‐frequency air temperature variations each contributed up to 5 Wm−2 variability in sensible heat flux. Latent heat flux was instead mostly driven by air humidity variability. Atmospheric gradients may result from convective structures or high‐frequency turbulent fluctuations. Comparisons with 0.05°‐resolution daily satellite SST observations demonstrate that remote sensing observations or lower‐resolution models may not capture the small‐scale spatial ocean variability present in the Atlantic trade wind region.

Enhanced Turbulent Mixing in the Upper Ocean Induced by Super Typhoon Goni (2015)

Based on the satellite-observed sea surface temperature (SST) data, high-resolution Argo observations and hybrid coordinate model (HYCOM) reanalysis results, this study examined the upper ocean response to Super Typhoon Goni in 2015 in the western north Pacific and revealed the significant diapycnal diffusivity enhancement in the upper ocean induced by Goni. Results indicate that the maximum SST cooling caused by Goni was 7.7 °C, which is greater than the SST cooling caused by most typhoons. The severe SST cooling was related to the enhancement of turbulent mixing induced by Goni. To the right of the typhoon track, the diapycnal diffusivity enhancement in the upper ocean caused by Goni could reach three orders of magnitude, from O (10−5 m2/s) to O (10−2 m2/s) and could last at least 9 days after the passage of Goni. In contrast, the diapycnal diffusivity to the left of the typhoon track did not show significant variations. The enhancement of turbulent mixing was found to be consistent with Goni-induced near-inertial kinetic energy calculated from the HYCOM reanalysis results, which suggests that the enhanced turbulent mixing was caused by Goni-induced near-inertial waves.

On the Response of Zhejiang Coastal Waters to 12 Typhoons from 2011 to 2015

Based on the hybrid coordinate ocean model (HYCOM) reanalysis data, the dynamical and thermal response of Zhejiang coastal waters to 12 typhoons from 2011 to 2015 was studied, and the relationship between the oceanic response and typhoon characteristics was analyzed. The HYCOM reanalysis data were validated by satellite-observed sea surface temperature data. Results show that all the 12 typhoons caused near-inertial waves, sea surface cooling and seafloor warming, but significant differences existed among them. Based on statistics, it was found that the domain-averaged near-inertial kinetic energy and seafloor warming are significantly correlated with the typhoon’s maximum wind speed, both of which show a positive relationship. The domain-averaged seafloor warming also decreases with the typhoon’s translation speed. Moreover, there exists a positive correlation between the domain-averaged sea surface cooling and seafloor warming. The different mechanisms that caused the seafloor warming for the 12 typhoons were also investigated in this study.

Understanding the Changing Nature of Marine Cold‐Spells

AbstractMarine cold‐spell (MCS) metrics—such as frequency and intensity—are decreasing globally, while marine heatwave (MHW) metrics are increasing due to sea surface temperature (SST) warming. However, the concomitant changes in MHW and MCS metrics, and whether SST warming can similarly explain the decreasing MCS metrics remain unclear. Here, we provide a comparative global assessment of these changes based on satellite SST observations over 1982–2020. Across the globe, we find distinct differences in mean MHW and MCS metrics. Furthermore, decreasing trends in MCS metrics are not necessarily aligned with increasing trends in MHW metrics. While differences in intensity trends are mainly explained by SST variance trends, differences in trends of annual days are less clear. Overall, decreasing MCS days and intensities are found to be largely driven by warming SST, rather than SST variance changes. Therefore, it is expected that MCS days and intensity will continue diminishing under global warming.

Application of Non-stationary Extreme Value Analysis to Satellite-Observed Sea Surface Temperature Data for Past Decades

Extreme value analysis (EVA) has been extensively used to understand and predict long-term return extreme values. This study provides the first approach to EVA using satellite-observed sea surface temperature (SST) data over the past decades. Representative EVA methods were compared to select an appropriate method to derive SST extremes of the East/Japan Sea (EJS). As a result, the peaks-over-threshold (POT) method showed better performance than the other methods. The Optimum Interpolation Sea Surface Temperature (OISST) database was used to calculate the 100-year-return SST values in the EJS. The calculated SST extremes were 1.60–3.44°C higher than the average value of the upper 5th-percentile satellite-observed SSTs over the past decades (1982–2018). The monthly distribution of the SST extremes was similar to the known seasonal variation of SSTs in the EJS, but enhanced extreme SSTs exceeding 2°C appeared in early summer and late autumn. The calculated 100-year-return SSTs were compared with the simulation results of the Coupled Model Intercomparison Project 5 (CMIP5) climate model. As a result, the extreme SSTs were slightly smaller than the maximum SSTs of the model data with a negative bias of –0.36°C. This study suggests that the POT method can improve our understanding of future oceanic warming based on statistical approaches using SSTs observed by satellites over the past decades.

Marine heatwaves of sea surface temperature off south Java

The frequency of marine heatwaves (MHWs) events has been rising globally in recent years, and this trend is expected to continue in the region off the coast of south Java Island. These oceanic extreme events may have the potential to devastate marine habitats, ecosystems and fisheries. This paper characterized MHWs off south Java from 1982 to 2019 using satellite-observed sea surface temperature. The aim of this study was to examine the dynamics of MHWs in one of Indonesia's most important fisheries hotspots, located in the southeast of the tropical Indian Ocean. We have identified two strong MHWs events in 1998 and 2016, both of which started in the austral winter months. Both events were lasted through the spring before dissipating in the early austral winter. These intense MHWs were likely related to a strong El Niño and decreased monsoon activity.

Impact of the Agulhas Current on southern Africa precipitation: a modelling study

AbstractThe Agulhas Current (AC) creates a sharp temperature gradient with the surrounding ocean, leading to a large turbulent flux of moisture from ocean to atmosphere. We use two simulations of the Weather Research and Forecasting (WRF) model to show the seasonal impact of the warm core of the AC on southern Africa precipitation. In one simulation the sea surface temperature (SST) of the AC is similar to satellite observations, while the second uses satellite SST observations spatially smoothed to reduce the temperature of the core of the AC by ~1.5°C. We show that decreasing the SST of the AC reduces the precipitation of the wettest seasons (austral summer and autumn) inland. Over the ocean, reducing the SST reduces precipitation, low-level wind convergence, SST and SLP Laplacian above the AC in all seasons, consistent with the pressure adjustment mechanism. Moreover, winter precipitation above the Current may be also related to increased latent flux. In summer and autumn, the AC SST reduction is also associated with decreased precipitation further inland (more than 1.5 mm/day), caused by an atmospheric circulation that decreases the horizontal moisture flux from the AC to South Africa. The reduction is also associated with higher geopotential height extending from the surface east and over the AC to the mid-troposphere over southeastern Africa. The westward tilted geopotential height is consistent with the linear response to shallow diabatic heating in midlatitudes. An identical mechanism occurs in spring but is weaker. Winter rainfall response is confined above the AC.

Recovery of Tropical Cyclone Induced SST Cooling Observed by Satellite in the Northwestern Pacific Ocean

Based on the satellite observed sea surface temperature (SST), the recovery of SST cooling induced by the tropical cyclones (TCs) over the northwestern Pacific Ocean is investigated. The results show that the passage of a TC induces a mean maximum cooling in the SST of roughly −1.25 °C. It was also found that most of this cooling (~87%) is typically erased within 30 days of TC passage. This recovery time depends upon the degree of cooling, with stronger (weaker) SST cooling corresponding to longer (shorter) recovery time. Further analyses show that the mixed layer depth (MLD) and the upper layer thermocline temperature gradient (UTTG) also play an important role in the SST response to TCs. The maximum cooling increases ~0.1 °C for every 7 m decrease in the MLD or every 0.04 °C/m increase in the UTTG. The combined effects of MLD and TC intensity and translation speed on the SST response are also discussed.

ХАРАКТЕРИСТИКИ АНТИЦИКЛОНИЧЕСКОГО ВИХРЯ, СФОРМИРОВАВШЕГОСЯ У ТИХООКЕАНСКОГО ПОБЕРЕЖЬЯ ЮЖНЫХ КУРИЛ ВЕСНОЙ 1999 г.

Based on the analysis of oceanographic survey materials and sea surface temperature satellite observations, the conditions of formation and characteristics of the anticyclonic eddy located in the region of the South Kuril Islands in the spring of 1999 were studied. It was shown that it separated from the subarctic front as result of its interaction with the Oyashio current stream in the second half of March and ceased to exist in mid-June, which is also confirmed by observations of the concentration of chlorophyll-a. In contrast the eddies formed as a result of meandering of the warm Kuroshio and Tsugaru currents, the eddy core, located at depths of 150–300 m, was characterized by lower values of temperature and salinity (4°–4.6°С and 33.55–33.65 е.п.с.) and low current velocities ( about 10 cm/s). The eddy was rather weakly distinguished in the density field both on horizontal and vertical distributions, as well as according to satellite altimetry data.

Sub-Surface Ocean Structure from Satellite Surface Observations in the North Indian Ocean

In this study interior plus Surface Quasi-Geostrophic (isQG) methodology is used to reconstruct subsurface density anomaly using sea surface temperature (SST), sea surface salinity (SSS) and sea surface height (SSH). The study is carried out in the Arabian Sea and Bay of Bengal of the Northern Indian ocean region. isQG is first tested for identical twin experiments, where the surface data and the stability profile (N2) were taken from a numerical ocean model. The root mean square error (RMSE) between isQG and model density anomalies lie within the error bars of model density anomaly in most of the levels. The impact of expected errors in synthetic observations of SST and SSS on isQG retrieved density anomalies was studied and it is found that error in SSS results in greater RMSE in isQG density anomaly profile in the Arabian sea than in the Bay of Bengal. isQG method is then applied to the satellite observations of SST, SSS and SSH and retrieved density profiles are then compared with model outputs and in-situ observations from RAMA buoy for the year 2019. The comparison indicates seasonal dependency and effect of N2 on the performance of isQG method.

Interannual Variability of the Wind-Wave Regime Parameters in the Black Sea

Purpose. The investigation is aimed at increasing accuracy of the temperature field reconstruction in the Black Sea upper layer. For this purpose, satellite observations of the sea surface temperature and the three-dimensional fields of temperature (in the 50–500 m layer) and salinity (in the 2.5–500 m layer) pseudo-measurements, previously calculated by the altimetry and the Argo floats data, were jointly assimilated in the Marine Hydrophysical Institute model. Methods and Results. Assimilation of the sea surface temperature satellite observations is the most effective instrument in case the discrepancies between the sea surface and the model temperatures are extrapolated over the upper mixed layer depth up to its lower boundary. Having been analyzed, the temperature profiles resulted from the forecast calculation for 2012 and from the Argo float measurements made it possible to obtain a simple criterion (bound to the model grid) for determining the upper mixed layer depth, namely the horizon on which the temperature gradient was less or equal to ≤ 0.017 °C/m. Within the upper mixed layer depth, the nudging procedure of satellite temperature measurements with the selected relaxation factor and the measurement errors taken into account was used in the heat transfer equation. The temperature and salinity pseudo-measurements were assimilated in the model by the previously proposed adaptive statistics method. To test the results of the sea surface temperature assimilation, the Black Sea hydrophysical fields were reanalyzed for 2012. The winter-spring period (January – April, December) is characterized by the high upper mixed layer depths, well reproducible by the Pacanowski – Philander parameterization, and also by the low values (as compared to the measured ones) of the basin-averaged monthly mean square deviations of the simulated temperature fields. The increased mean square deviations in July – September are explained by absence of the upper mixed layer in the temperature profiles measured by the Argo floats that is not reproduced by the Pacanowski – Philander parameterization. Conclusions. The algorithm for assimilating the sea surface temperature together with the profiles of the temperature and salinity pseudo-measurements reconstructed from the altimetry data was realized. Application of the upper mixed layer depths estimated by the temperature vertical profiles made it possible to correct effectively the model temperature by the satellite-derived sea surface temperature, especially for a winter-spring period. It permitted to reconstruct the temperature fields in the sea upper layer for 2012 with acceptable accuracy.

Vosstanovleniye gidrofizicheskikh poley Chernogo morya s assimilyatsiyey poverkhnostnoy temperatury i psevdoizmereniy temperatury, solenosti v modeli

Purpose. The investigation is aimed at increasing accuracy of the temperature field reconstruction in the Black Sea upper layer. For this purpose, satellite observations of the sea surface temperature and the three-dimensional fields of temperature (in the 50–500 m layer) and salinity (in the 2.5–500 m layer) pseudo-measurements, previously calculated by the altimetry and the Argo floats data, were jointly assimilated in the Marine Hydrophysical Institute model. Methods and Results. Assimilation of the sea surface temperature satellite observations is the most effective instrument in case the discrepancies between the sea surface and the model temperatures are extrapolated over the upper mixed layer depth up to its lower boundary. Having been analyzed, the temperature profiles resulted from the forecast calculation for 2012 and from the Argo float measurements made it possible to obtain a simple criterion (bound to the model grid) for determining the upper mixed layer depth, namely the horizon on which the temperature gradient was less or equal to 0.017°C/m. Within the upper mixed layer depth, the nudging procedure of satellite temperature measurements with the selected relaxation factor and the measurement errors taken into account was used in the heat transfer equation. The temperature and salinity pseudo-measurements were assimilated in the model by the previously proposed adaptive statistics method. To test the results of the sea surface temperature assimilation, the Black Sea hydrophysical fields were reanalyzed for 2012. The winterspring period (January – April, December) is characterized by the high upper mixed layer depths, well reproducible by the Pacanowsci – Philander parameterization, and also by the low values (as compared to the measured ones) of the basin-averaged monthly mean square deviations of the simulated temperature fields. The increased mean square deviations in July – September are explained by absence of the upper mixed layer in the temperature profiles measured by the Argo floats that is not reproduced by the Pacanowsci – Philander parameterization. Conclusions. The algorithm for assimilating the sea surface temperature together with the profiles of the temperature and salinity pseudo-measurements reconstructed from the altimetry data was realized. Application of the upper mixed layer depths estimated by the temperature vertical profiles made it possible to correct effectively the model temperature by the satellite-derived sea surface temperature, especially for a winter-spring period. It permitted to reconstruct the temperature fields in the sea upper layer for 2012 with acceptable accuracy.